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frameworks to maximise compression ratios. We will use predictor models which estimate projections or slices, storing only differences between the prediction and original data. Because errors are small and
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | about 1 month ago
Shi, Andrew Cunningham, and Ferenc Huszár. Lossy Image Compression with Compressive Autoencoders. In International Conference on Learning Representations (ICLR), Toulon, France, 2017. [7] S. Valette and
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analysis in the area of magnetic resonance imaging (MRI) and positron emission tomography (PET); Minimum Level 1 certification in Cardiac Computed Tomography (CT) and/or Cardiac Magnetic Resonance Imaging
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encompasses model compression and optimization for edge deployment on UAV-mounted processors to support real-time inference. The candidate will collaborate with industrial partners for real-world data
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sustainable machine learning approaches and addressing renewable energy related projects. Likewise, deploying a novel paradigm of KGML (knowledge guided machine learning) can propel further research. PhD